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Effective Statistical Learning Methods for Actuaries III - Neural Networks and Extensions (Paperback, 1st ed. 2019)
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Effective Statistical Learning Methods for Actuaries III - Neural Networks and Extensions (Paperback, 1st ed. 2019)
Series: Springer Actuarial
Expected to ship within 10 - 15 working days
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This book reviews some of the most recent developments in neural
networks, with a focus on applications in actuarial sciences and
finance. It simultaneously introduces the relevant tools for
developing and analyzing neural networks, in a style that is
mathematically rigorous yet accessible. Artificial intelligence and
neural networks offer a powerful alternative to statistical methods
for analyzing data. Various topics are covered from feed-forward
networks to deep learning, such as Bayesian learning, boosting
methods and Long Short Term Memory models. All methods are applied
to claims, mortality or time-series forecasting. Requiring only a
basic knowledge of statistics, this book is written for masters
students in the actuarial sciences and for actuaries wishing to
update their skills in machine learning. This is the third of three
volumes entitled Effective Statistical Learning Methods for
Actuaries. Written by actuaries for actuaries, this series offers a
comprehensive overview of insurance data analytics with
applications to P&C, life and health insurance. Although
closely related to the other two volumes, this volume can be read
independently.
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